cut {base} | R Documentation

## Convert Numeric to Factor

### Description

`cut` divides the range of `x` into intervals and codes the values in `x` according to which interval they fall. The leftmost interval corresponds to level one, the next leftmost to level two and so on.

### Usage

    cut(x, ...)

    ## Default S3 method:
    cut(x, breaks, labels = NULL,
        include.lowest = FALSE, right = TRUE, dig.lab = 3, ...)

### Arguments

`x` | a numeric vector which is to be converted to a factor by cutting.
`breaks` | either a vector of cut points or number giving the number of intervals which `x` is to be cut into.
`labels` | labels for the levels of the resulting category. By default, labels are constructed using `"(a,b]"` interval notation. If `labels = FALSE`, simple integer codes are returned instead of a factor.
`include.lowest` | logical, indicating if an ‘x[i]’ equal to the lowest (or highest, for `right = FALSE`) ‘breaks’ value should be included.
`right` | logical, indicating if the intervals should be closed on the right (and open on the left) or vice versa.
`dig.lab` | integer which is used when labels are not given. It determines the number of digits used in formatting the break numbers.
`...` | further arguments passed to or from other methods.

### Details

If a `labels` parameter is specified, its values are used to name the factor levels. If none is specified, the factor level labels are constructed as `"(b1, b2]"`, `"(b2, b3]"` etc. for `right=TRUE` and as `"[b1, b2)"`, ... if `right=FALSE`. In this case, `dig.lab` indicates how many digits should be used in formatting the numbers `b1`, `b2`, ....

### Value

A `factor` is returned, unless `labels = FALSE` which results in the mere integer level codes.

### Note

Instead of `table(cut(x, br))`, `hist(x, br, plot = FALSE)` is more efficient and less memory hungry. Instead of `cut(*, labels = FALSE)`, `findInterval()` is more efficient.

### References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

### See Also

`split` for splitting a variable according to a group factor; `factor`, `tabulate`, `table`, `findInterval()`.

### Examples

    Z <- rnorm(10000)
    table(cut(Z, br = -6:6))
    sum(table(cut(Z, br = -6:6, labels=FALSE)))
    sum(   hist  (Z, br = -6:6, plot=FALSE)$counts)

    cut(rep(1,5),4)#-- dummy
    tx0 <- c(9, 4, 6, 5, 3, 10, 5, 3, 5)
    x <- rep(0:8, tx0)
    stopifnot(table(x) == tx0)

    table( cut(x, b = 8))
    table( cut(x, br = 3*(-2:5)))
    table( cut(x, br = 3*(-2:5), right = FALSE))

    ##--- some values OUTSIDE the breaks :
    table(cx  <- cut(x, br = 2*(0:4)))
    table(cxl <- cut(x, br = 2*(0:4), right = FALSE))
    which(is.na(cx));  x[is.na(cx)]  #-- the first 9  values  0
    which(is.na(cxl)); x[is.na(cxl)] #-- the last  5  values  8

    ## Label construction:
    y <- rnorm(100)
    table(cut(y, breaks = pi/3*(-3:3)))
    table(cut(y, breaks = pi/3*(-3:3), dig.lab=4))

    table(cut(y, breaks =  1*(-3:3), dig.lab=4))# extra digits don't "harm" here
    table(cut(y, breaks =  1*(-3:3), right = FALSE))#- the same, since no exact INT!

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